Skip to main content
SpringerLink
Log in

Knowledge Representation and Ontologies

  • Chapter
  • First Online:
Clinical Research Informatics

Part of the book series: Health Informatics ((HI))

Abstract

Ontologies have become important tools in biomedicine, supporting ­critical aspects of both health care and biomedical research, including clinical research. Some even see ontologies as integral to science. Unlike terminologies (focusing on naming) and classification systems (developed for partitioning a domain), ontologies define the types of entities that exist, as well as their ­interrelations. And while knowledge bases generally integrate both definitional and assertional knowledge, ontologies focus on what is always true of entities, i.e., ­definitional knowledge. In practice, however, there is no sharp distinction between these kinds of artifacts, and ontology has become a generic name for a variety of knowledge sources with important differences in their degree of formality, ­coverage, richness, and computability. In this chapter, we focus on those ontologies of ­particular relevance to clinical research. After a brief introduction to ontology ­development and knowledge representation, we present the characteristics of some of these ontologies. We then show how ontologies are integrated in and made accessible through knowledge repositories and illustrate their role in clinical research.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 119.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bodenreider O. Biomedical ontologies in action: role in knowledge management, data integration and decision support. Yearb Med Inform. 2008;47:67–79.

    Google Scholar 

  2. Smith B. Ontology (science). 2008. Nature precedings Available from Nature Precedings (http://hdl.handle.net/10101/npre.2008.2027.2). Accessed Aug 2011.

  3. Bodenreider O, Stevens R. Bio-ontologies: current trends and future directions. Brief Bioinform. 2006;7:256–74.

    Article  PubMed  CAS  Google Scholar 

  4. Cimino JJ. Zhu X. The practical impact of ontologies on biomedical informatics. Yearb Med Inform. 2006;45:124–35.

    Google Scholar 

  5. Smith B, Ceusters W, Klagges B, Kohler J, Kumar A, Lomax J, Mungall C, Neuhaus F, Rector AL, Rosse C. Relations in biomedical ontologies. Genome Biol. 2005;6:R46.

    Article  PubMed  Google Scholar 

  6. Simmons P, Melia J. Continuants and occurrents. Proc Aristotelian Soc. 2000;74:59–75, 77–92.

    Article  Google Scholar 

  7. BFO. http://www.ifomis.org/bfo/. Accessed Aug 2011.

  8. DOLCE. http://www.loa-cnr.it/DOLCE.html. Accessed Aug 2011.

  9. McCray AT. An upper-level ontology for the biomedical domain. Comp Funct Genomics. 2003;4:80–4.

    Article  PubMed  Google Scholar 

  10. Beißwanger E, Schulz S, Stenzhorn H, Hahn U. BioTop: an upper domain ontology for the life sciences - a description of its current structure, contents, and interfaces to OBO ontologies. Appl Ontol. 2008;3:205–12.

    Google Scholar 

  11. Baader F, Calvanese D, McGuinness D, Nardi D, Patel-Schneider P, editors. The description logic handbook: theory, implementation, and applications. Cambridge/New York: Cambridge University Press; 2007.

    Google Scholar 

  12. Berners-Lee T, Hendler J, Lassila O. The semantic web: a new form of Web content that is meaningful to computers will unleash a revolution of new possibilities. Sci Am. 2001;284:34–43.

    Article  Google Scholar 

  13. OWL 2 web ontology language document overview. http://www.w3.org/TR/owl2-overview/. Accessed Aug 2011.

  14. RDF vocabulary description language 1.0: RDF schema. http://www.w3.org/TR/rdf-schema/. Accessed Aug 2011.

  15. SKOS simple knowledge organization system reference. http://www.w3.org/TR/2009/REC-skos-reference-20090818/. Accessed Aug 2011.

  16. The OBO flat file format specification. http://www.geneontology.org/GO.format.obo-1_2.shtml. Accessed Aug 2011.

  17. Golbreich C, Horridge M, Horrocks I, Motik B, Shearer R. OBO and OWL: leveraging semantic web technologies for the life sciences. In: Proceedings of the 6th international the semantic web and 2nd Asian conference on Asian semantic web conference. Busan: Springer; 2007. p. 169–82.

    Google Scholar 

  18. Noy N, Tudorache T, Nyulas C, Musen M. The ontology life cycle: integrated tools for editing, publishing, peer review, and evolution of ontologies. AMIA Annu Symp Proc. 2010;2010:552–6.

    PubMed  Google Scholar 

  19. Protégé. http://protege.stanford.edu/. Accessed Aug 2011.

  20. Day-Richter J, Harris MA, Haendel M, Lewis S. OBO-edit – an ontology editor for biologists. Bioinformatics. 2007;23:2198–200.

    Article  PubMed  CAS  Google Scholar 

  21. OBO-edit. http://oboedit.org/. Accessed Aug 2011.

  22. Smith B, Ashburner M, Rosse C, Bard J, Bug W, Ceusters W, Goldberg LJ, Eilbeck K, Ireland A, Mungall CJ, Leontis N, Rocca-Serra P, Ruttenberg A, Sansone SA, Scheuermann RH, Shah N, Whetzel PL, Lewis S. The OBO foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol. 2007;25:1251–5.

    Article  PubMed  CAS  Google Scholar 

  23. Harmonization. http://www.ihtsdo.org/about-ihtsdo/harmonization/. Accessed Aug 2011.

  24. Richesson RL, Krischer J. Data standards in clinical research: gaps, overlaps, challenges and future directions. J Am Med Inform Assoc. 2007;14:687–96.

    Article  PubMed  Google Scholar 

  25. Shankar RD, Martins SB, O’Connor M, Parrish DB, Das AK. An ontology-based architecture for integration of clinical trials management applications. AMIA Annu Symp Proc. 2007;2007:661–5.

    Google Scholar 

  26. Shankar R, Arkalgud S. Connor M, Boyce K, Parrish D, Das A. TrialWiz: an ontology-driven tool for authoring clinical trial protocols. AMIA Annu Symp Proc. 2008:1226.

    Google Scholar 

  27. Tu SW, Fridsma DB, Shankar R, Connor M, Das A, Parrish D. Bridging epoch: mapping two clinical trial ontologies. In: 10th international protege conference. Budapest; 2007.

    Google Scholar 

  28. Tu SW, Carini S, Rector A, Maccalum P, Toujilov I, Harris S, Sim I. OCRe: ontology of clinical research. In: 11th international protege conference. Amsterdam; 2009.

    Google Scholar 

  29. The OBI Consortium. http://obi-ontology.org/page/Consortium. Accessed Aug 2011.

  30. Whetzel PL, Brinkman RR, Causton HC, Fan L, Field D, Fostel J, Fragoso G, Gray T, Heiskanen M, Hernandez-Boussard T, Morrison N, Parkinson H, Rocca-Serra P, Sansone SA, Schober D, Smith B, Stevens R, Stoeckert Jr CJ, Taylor C, White J, Wood A. Development of FuGO: an ontology for functional genomics investigations. OMICS. 2006;10:199–204.

    Article  PubMed  CAS  Google Scholar 

  31. Brinkman RR, Courtot M, Derom D, Fostel JM, He Y, Lord P, Malone J, Parkinson H, Peters B, Rocca-Serra P, Ruttenberg A, Sansone SA, Soldatova LN, Stoeckert Jr CJ, Turner JA, Zheng J. Modeling biomedical experimental processes with OBI. J Biomed Semantics. 2010;1 Suppl 1:S7.

    PubMed  Google Scholar 

  32. de Coronado S, Haber MW, Sioutos N, Tuttle MS, Wright LW. NCI Thesaurus: using science-based terminology to integrate cancer research results. Medinfo. 2004;11:33–7.

    Google Scholar 

  33. Sioutos N, de Coronado S, Haber MW, Hartel FW, Shaiu WL, Wright LW. NCI Thesaurus: a semantic model integrating cancer-related clinical and molecular information. J Biomed Inform. 2007;40:30–43.

    Article  PubMed  CAS  Google Scholar 

  34. Fragoso G, de Coronado S, Haber M, Hartel F, Wright L. Overview and utilization of the NCI Thesaurus. Comp Funct Genomics. 2004;5:648–54.

    Article  PubMed  CAS  Google Scholar 

  35. SNOMED CT (systematized nomenclature of medicine-clinical terms). http://www.ihtsdo.org/our-standards/. Accessed Aug 2011.

  36. Blumenthal D, Tavenner M. The “meaningful use” regulation for electronic health records. N Engl J Med. 2010;363:501–4.

    Article  PubMed  CAS  Google Scholar 

  37. Office of the National Coordinator for Health Information Technology (ONC) - Department of Health and Human Services. Standards & certification criteria interim final rule: revisions to initial set of standards, implementation specifications, and certification criteria for electronic health record technology. Fed Regist. 2010;75:62686–90.

    Google Scholar 

  38. Brown SH, Elkin PL, Rosenbloom ST, Husser C, Bauer BA, Lincoln MJ, Carter J, Erlbaum M, Tuttle MS. VA National Drug File Reference Terminology: a cross-institutional content coverage study. Stud Health Technol Inform. 2004;107:477–81.

    PubMed  Google Scholar 

  39. Rosenbloom ST, Awad J, Speroff T, Elkin PL, Rothman R, Spickard 3rd A, Peterson J, Bauer BA, Wahner-Roedler DL, Lee M, Gregg WM, Johnson KB, Jirjis J, Erlbaum MS, Carter JS, Lincoln MJ, Brown SH. Adequacy of representation of the National Drug File Reference Terminology physiologic effects reference hierarchy for commonly prescribed medications. AMIA Annu Symp Proc. 2003;2003:569–78.

    Google Scholar 

  40. National Drug File Reference Terminology. ftp://ftp1.nci.nih.gov/pub/cacore/EVS/NDF-RT/. Accessed on 13 Dec 2011

  41. National Library of Medicine: (RxNav), http://rxnav.nlm.nih.gov/. Accessed on 13 Dec 2011

  42. Cimino JJ, Ayres EJ. The clinical research data repository of the US National Institutes of Health. Stud Health Technol Inform. 2010;160:1299–303.

    PubMed  Google Scholar 

  43. Lowe HJ, Ferris TA, Hernandez PM, Weber SC. STRIDE – an integrated standards-based translational research informatics platform. AMIA Annu Symp Proc. 2009;2009:391–5.

    PubMed  Google Scholar 

  44. Ruttenberg A, Clark T, Bug W, Samwald M, Bodenreider O, Chen H, Doherty D, Forsberg K, Gao Y, Kashyap V, Kinoshita J, Luciano J, Marshall MS, Ogbuji C, Rees J, Stephens S, Wong GT, Wu E, Zaccagnini D, Hongsermeier T, Neumann E, Herman I, Cheung KH. Methodology – advancing translational research with the Semantic Web. BMC Bioinformatics. 2007;8:S2.

    Article  PubMed  Google Scholar 

  45. McCusker JP, Phillips JA, Gonzalez Beltran A, Finkelstein A, Krauthammer M. Semantic web data warehousing for caGrid. BMC Bioinformatics. 2009;10 Suppl 10:S2.

    Article  PubMed  Google Scholar 

  46. Sahoo SS, Bodenreider O, Rutter JL, Skinner KJ, Sheth AP. An ontology-driven semantic mashup of gene and biological pathway information: application to the domain of nicotine dependence. J Biomed Inform. 2008;41:752–65.

    Article  PubMed  CAS  Google Scholar 

  47. Translational medicine ontology and knowledge base. www.w3.org/wiki/HCLSIG/PharmaOntology. Accessed Aug 2011.

  48. Humphreys BL, Lindberg DA, Hole WT. Assessing and enhancing the value of the UMLS knowledge sources. Proc Annu Symp Comput Appl Med Care. 1991:78–82.

    Google Scholar 

  49. Humphreys BL, Lindberg DA, Schoolman HM, Barnett GO. The unified medical language system: an informatics research collaboration. J Am Med Inform Assoc. 1998;5:1–11.

    Article  PubMed  CAS  Google Scholar 

  50. Lindberg DA, Humphreys BL, McCray AT. The unified medical language system. Methods Inf Med. 1993;32:281–91.

    PubMed  CAS  Google Scholar 

  51. Bodenreider O. The unified medical language system (UMLS): integrating biomedical terminology. Nucleic Acids Res. 2004;32(Database issue):D267–70.

    Article  PubMed  CAS  Google Scholar 

  52. Unified medical language system (UMLS), http://www.nlm.nih.gov/research/umls/. Accessed Aug 2011.

  53. McCray AT, Srinivasan S, Browne AC. Lexical methods for managing variation in biomedical terminologies. Proc Annu Symp Comput Appl Med Care. 1994:235–9.

    Google Scholar 

  54. Fung KW, Bodenreider O. Utilizing the UMLS for semantic mapping between terminologies. AMIA Annu Symp Proc. 2005;2005:266–70.

    Google Scholar 

  55. Aronson AR. Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program. Proc AMIA Symp. 2001:17–21.

    Google Scholar 

  56. Aronson AR, Lang FM. An overview of MetaMap: historical perspective and recent advances. J Am Med Inform Assoc. 2010;17:229–36.

    PubMed  Google Scholar 

  57. Fung KW, Hole WT, Srinivasan S. Who is using the UMLS and how – insights from the UMLS user annual reports. AMIA Annu Symp Proc. 2006:274–8.

    Google Scholar 

  58. Noy NF, Shah NH, Whetzel PL, Dai B, Dorf M, Griffith N, Jonquet C, Rubin DL, Storey MA, Chute CG, Musen MA. BioPortal: ontologies and integrated data resources at the click of a mouse. Nucleic Acids Res. 2009;37:W170–3.

    Article  PubMed  CAS  Google Scholar 

  59. Ghazvinian A, Noy NF, Musen MA. Creating mappings for ontologies in biomedicine: simple methods work. AMIA Annu Symp Proc. 2009;2009:198–202.

    PubMed  Google Scholar 

  60. Weiler G, Brochhausen M, Graf N, Schera F, Hoppe A, Kiefer S. Ontology based data management systems for post-genomic clinical trials within a European Grid Infrastructure for Cancer Research. Conf Proc IEEE Eng Med Biol Soc. 2007;2007:6435–8.

    PubMed  Google Scholar 

  61. ACGT master ontology. http://www.ifomis.org/wiki/ACGT_Master_Ontology_%28MO%29. Accessed Aug 2011.

  62. Genome-wide association studies. http://grants.nih.gov/grants/gwas/. Accessed on 13 Dec 2011

  63. Bodenreider O. Ontologies and data integration in biomedicine: success stories and challenging issues. In: Bairoch A, Cohen-Boulakia S, Froidevaux C, editors. Proceedings of the fifth international workshop on data integration in the life sciences (DILS 2008), vol. LNBI 5109. Berlin/Heidelberg/New York: Springer; 2008. p. 1–4.

    Google Scholar 

  64. Biomedical informatics research network. http://www.birncommunity.org/tools-catalog/neurolex-formerly-birnlex/. Accessed on 13 Dec 2011

  65. Rubin DL, Shah NH, Noy NF. Biomedical ontologies: a functional perspective. Brief Bioinform. 2008;9:75–90.

    Article  PubMed  Google Scholar 

  66. Cook C, Hannley M, Richardson JK, Michon J, Harker M, Pietrobon R. Real-time updates of meta-analyses of HIV treatments supported by a biomedical ontology. Account Res. 2007;14:1–18.

    PubMed  Google Scholar 

  67. Shah NH, Jonquet C, Chiang AP, Butte AJ, Chen R, Musen MA. Ontology-driven indexing of public datasets for translational bioinformatics. BMC Bioinformatics. 2009;10 Suppl 2:S1.

    Article  PubMed  Google Scholar 

  68. Bizer C, Heath T, Berners-Lee T. Linked data – the story so far. Int J Semant Web Inf. 2009;5:1–22.

    Google Scholar 

  69. HCLS: Semantic Web Health Care and Life Sciences (HCLS) Interest Group. (HCLS), http://www.w3.org/wiki/HCLSIG/. Accessed on 13 Dec 2011

  70. Linking open drug data. http://www.w3.org/wiki/HCLSIG/LODD. Accessed Aug 2011.

  71. Rosse C, Shapiro LG, Brinkley JF. The digital anatomist foundational model: principles for defining and structuring its concept domain. Proc AMIA Symp. 1998:820–4.

    Google Scholar 

  72. Rubin DL, Dameron O, Bashir Y, Grossman D, Dev P, Musen MA. Using ontologies linked with geometric models to reason about penetrating injuries. Artif Intell Med. 2006;37:167–76.

    Article  PubMed  Google Scholar 

  73. Rubin DL, Dameron O, Musen MA. Use of description logic classification to reason about consequences of penetrating injuries. AMIA Annu Symp Proc.2005:649–53.

    Google Scholar 

  74. Mabotuwana T, Warren J. An ontology-based approach to enhance querying capabilities of general practice medicine for better management of hypertension. Artif Intell Med. 2009;47:87–103.

    Article  PubMed  Google Scholar 

  75. Goldstein MK, Hoffman BB, Coleman RW, Tu SW, Shankar RD, O’Connor M, Martins S, Advani A, Musen MA. Patient safety in guideline-based decision support for hypertension management: ATHENA DSS. Proc AMIA Symp. 2001:214–8.

    Google Scholar 

Download references

Acknowledgments

This research was supported in part by the Intramural Research Program of the National Institutes of Health (NIH), National Library of Medicine (NLM).

Author information

Authors and Affiliations

  1. Lister Hill National Center for Biomedical Communications, US National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD, 20894, USA

    Kin Wah Fung M.D., M.S., M.A. & Olivier Bodenreider M.D., Ph.D.

Authors
  1. Kin Wah Fung M.D., M.S., M.A.
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Olivier Bodenreider M.D., Ph.D.
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kin Wah Fung M.D., M.S., M.A. .

Editor information

Editors and Affiliations

  1. College of Medicine, University of South Florida, Bruce B. Downs Blvd. 12901, Tampa, 33612-4799, Florida, USA

    Rachel L. Richesson

  2. College of Medicine, University of South Florida, Bruce B. Downs Blvd. 12901, Tampa, 33612-4799, Florida, USA

    James E. Andrews

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag London Limited

About this chapter

Cite this chapter

Fung, K.W., Bodenreider, O. (2012). Knowledge Representation and Ontologies. In: Richesson, R., Andrews, J. (eds) Clinical Research Informatics. Health Informatics. Springer, London. https://doi.org/10.1007/978-1-84882-448-5_14

Download citation

  • DOI: https://doi.org/10.1007/978-1-84882-448-5_14

  • Published:

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84882-447-8

  • Online ISBN: 978-1-84882-448-5

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics

Search

Navigation